{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T00:08:15Z","timestamp":1785370095118,"version":"3.55.0"},"reference-count":23,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T00:00:00Z","timestamp":1741651200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cytopathology"],"published-print":{"date-parts":[[2025,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Introduction<\/jats:title><jats:p>Recent studies have shown that digital cytology (DC) coupled with artificial intelligence (AI) algorithms is a valid approach to the diagnosis of cervico\u2010vaginal lesions using liquid\u2010based cytology (LBC). We evaluated the use of these methods for anal LBC specimens.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A series of 124 anal LBC slides previously diagnosed by conventional microscopy (CC) were reviewed with a DC\/AI system that generated a gallery of images. Diagnoses based on the selected images, according to the 2014 Bethesda System for Reporting Cervical Cytology, were compared to CC.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Overall, CC and DC\/AI approaches detected a similar number of abnormal (ASC\u2010US+) cases (63 and 62 cases, respectively). We observed an exact concordance between CC and DC in 70 (57.9%) cases, corresponding to a moderate agreement between the two approaches (\u03ba\u2009=\u20090.41, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001). A moderate agreement (\u03ba\u2009=\u20090.48, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001) was also found when positive cases were stratified into \u2018low\u2010grade\u2019 (ASC\u2010US, LSIL) and \u2018high\u2010grade\u2019 lesions (ASC\u2010H, HSIL). The DC\/AI system detected more cases of higher severity (ASC\u2010H, HSIL: 9 and 2 cases, respectively) than CC (3 cases classified as HSIL).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The number of ASC\u2010US+ cases detected by both systems was similar. The DC\/AI system detected more cases of higher severity compared to the CC.<\/jats:p><\/jats:sec>","DOI":"10.1111\/cyt.13482","type":"journal-article","created":{"date-parts":[[2025,3,12]],"date-time":"2025-03-12T09:09:10Z","timestamp":1741770550000},"page":"250-258","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Digital Cytology Combined With Artificial Intelligence Compared to Conventional Microscopy for Anal Cytology: A Preliminary Study"],"prefix":"10.1111","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-4382-9791","authenticated-orcid":false,"given":"Ren\u00ea","family":"Gerhard","sequence":"first","affiliation":[{"name":"Centre National de Pathologie Laboratoire National de Sant\u00e9  Dudelange Luxembourg"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cioly Rivero","family":"Colmenarez","sequence":"additional","affiliation":[{"name":"Centre National de Pathologie Laboratoire National de Sant\u00e9  Dudelange Luxembourg"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Corinne","family":"Selle","sequence":"additional","affiliation":[{"name":"Centre National de Pathologie Laboratoire National de Sant\u00e9  Dudelange Luxembourg"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5798-9548","authenticated-orcid":false,"given":"Ga\u00ebl Paul","family":"Hammer","sequence":"additional","affiliation":[{"name":"Centre National de Pathologie Laboratoire National de Sant\u00e9  Dudelange 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